Block chain method and system for securing user data from an on-line course

ABSTRACT

In an example, the present invention provides a meta data processing apparatus for processing sensor inputs and providing feedback to a user for an on-line course. The invention provides for storing the information on a public block chain using a plurality of servers.

CROSS REFERENCE TO RELATED PATENT APPLICATION

This application is a continuation of and claims priority to U.S.application Ser. No. 16/254,316, filed Jan. 22, 2019, which claimspriority to U.S. Provisional Patent Application No. 62/620,376, filed onJan. 22, 2018, which are hereby incorporated by reference in theirentirety.

BACKGROUND OF INVENTION

The present invention relates generally to processing techniques forcourse materials. In particular, the invention provides a method andsystem for using a block chain configured on a public ledge for securinguser information associated with an on-line course, a certification ordegree, or other information in the field of education. Moreparticularly, the invention provides a method and system using datacapturing devices configured with artificial intelligence techniques,and then securing storing a certification associated with a learningprocess associated with such method and system. Merely by way ofexample, the invention has been applied to a mobile computing deviceconfigured to a world wide network of computers, however, the inventionhas many other applications.

“Education is the process of facilitating learning, or the acquisitionof knowledge, skills, values, beliefs, and habits. Educational methodsinclude storytelling, discussion, teaching, training, and directedresearch. Education frequently takes place under the guidance ofeducators, but learners may also educate themselves. Education can takeplace in formal or informal settings and any experience that has aformative effect on the way one thinks, feels, or acts may be considerededucational. The methodology of teaching is called pedagogy.”https://en.wikipedia.org/wiki/Education.

Education originally occurred through a one by one basis between teacherand student or master and apprentice or partner and associate.Classrooms eventually took over to teach children in masses frompre-school to higher education. Most recently, education has beenimplemented on-line via the Internet to facilitate learning forstudents. Although education has progressed, it is desired thattechniques to overcome difficulties in education, and more particularlylearning are desired.

SUMMARY

According to the present invention, techniques related to coursematerials. In particular, the invention provides a method for using ablock chain configured on a public ledge for securing user informationassociated with an on-line course, a certification or degree, or otherinformation in the field of education. More particularly, the inventionprovides a method and system using data capturing devices configuredwith artificial intelligence techniques, and then securing storing acertification associated with a learning process associated with suchmethod and system. Merely by way of example, the invention has beenapplied to a mobile computing device configured to a world wide networkof computers, however, the invention has many other applications.

In an example, the present invention provides a meta data processingapparatus for processing sensor inputs and providing feedback to a userfor an on-line course. The apparatus has a housing configured with adisplay device. In an example, the display device is coupled to an inputdevice for communicating text information from a user. The device has aprocessing device, such as a central processing unit, graphicsprocessing unit, digital signal processing unit, micro controller orothers.

In an example, the apparatus has a network interface coupled to theprocessing device. In an example, the network interface is configured tocouple to a world wide network of computers or a local network ofcomputers. The apparatus has a memory resource coupled to the processingdevice and an application comprising a course module. In an example, thecourse module comprises a plurality of templates and at least one videofile, and processes, each of which may be desirably tailored to a userbased upon feedback from various processing modules.

In an example, the apparatus has an image capturing device coupled tothe housing and configured to the processing device. In an example, theimage capturing device is configured to capture an image of at least afacial expression in a first format of the user while interacting withthe course module. The image capturing device can be a high-resolutioncamera that is suitable for capturing the image and has sufficientpixels to be processed.

In an example, the apparatus has a plurality of sensors for identifyinga spatial orientation of the user while interacting with the coursemodule. In an example, the sensor devices or plurality of external datacapturing devices comprises a camera, a keyboard, an accelerometersensor, an rf sensor, a gyroscope, a chemical sensor, a temperaturesensor, a microphone, or other input device. Of course, there can beother variations, modifications, and alternatives.

In various embodiments, the apparatus may include a mixed reality orvirtual reality headset that captures the user data using sensors fromwithin a headset (e.g. Microsoft HoloLens and Mixed Reality platform,Magic Leap platform, Google Daydream, etc.) or that captures user datafrom a headset using external sensors, (e.g. HTC Vive, Oculus Rift)Various embodiments of headsets may provide spatial orientation dataincluding where the user is viewing within an image (e.g. a lecturer,white board, etc.), where they are gazing within an image (e.g.equation, graph or diagram, etc.), duration of time viewing materials(e.g. reading a slide, or .pdf, etc.); voice data (e.g. a user repeatinga foreign language phrase); and the like.

In an example, the apparatus has a natural language processor configuredfor processing information from the text information while the user isinteracting with the course module. In an example, the natural languageprocessor is configured to process the text information to identify acharacteristic of the user in association with the course. Additionally,the apparatus has an artificial intelligence module coupled to theprocessing device. In an example, the artificial intelligence modulecomprises a neural network module comprising a plurality of nodes. In anexample, the plurality of nodes can be numbered from 1-N, where N is aninteger greater than 10 and less than 10,000,000, and possibly greater,depending upon the example. The plurality of nodes are coupled torespective sensors, image capturing device, natural language processor,or other information receiving devices, and an output. Of course, therecan be other variations, modifications, and alternatives.

In an example, the apparatus has an output handler coupled to the outputof the neural network module, the output handler configured to providefeedback to the user. The feedback comprises a plurality ofcharacteristics to allow the user to achieve a predetermined scorewithin a range for the course.

The above examples and implementations are not necessarily inclusive orexclusive of each other and may be combined in any manner that isnon-conflicting and otherwise possible, whether they be presented inassociation with a same, or a different, embodiment or example orimplementation. The description of one embodiment or implementation isnot intended to be limiting with respect to other embodiments and/orimplementations. Also, any one or more function, step, operation, ortechnique described elsewhere in this specification may, in alternativeimplementations, be combined with any one or more function, step,operation, or technique described in the summary. Thus, the aboveexamples implementations are illustrative, rather than limiting.

DESCRIPTION OF THE DRAWINGS

FIG. 1A is a simplified diagram of a meta processing system for learningaccording to an example of the present invention.

FIG. 1 is a simplified diagram with a network system according to anexample of the present invention.

FIG. 2 is a more detailed diagram of a processing engine with inputdevices according to an example of the present invention.

FIG. 3 is a more detailed diagram of a processing system according to anexample of the present invention.

FIG. 4 is a more detailed diagram of an alternative processing systemaccording to an example of the present invention.

FIG. 5 is a more detailed diagram of an alternative processing systemaccording to an example of the present invention.

FIG. 6 is a simplified flow diagram of an integrated data processingprocess according to an example of the present invention.

DETAILED DESCRIPTION OF THE EXAMPLES

According to the present invention, techniques related to coursematerials are provided. In particular, the invention provides a methodand system for using a block chain configured on a public ledge forsecuring user information associated with an on-line course, acertification or degree, or other information in the field of education.More particularly, the invention provides a method and system using datacapturing devices configured with artificial intelligence techniques,and then securing storing a certification associated with a learningprocess associated with such method and system. Merely by way ofexample, the invention has been applied to a mobile computing deviceconfigured to a world wide network of computers, however, the inventionhas many other applications.

In an example, one or more of the definitions may be used in thefollowing description of the specification.

EIs or Education Institutions means a non-profit, for-profitorganizations, or entitie(s) that offer education or training.

IACs or Institutional Accreditation Credentials means verified receiptof passed reviews or diligence by qualified bodies, as defined by therelevant society, committee, regulatory agency, non profit body orentity, to the field of learning, standards, or other regulatory body.

EPs or Educational Products means courses or other educationalofferings.

LIs means Learner Identification.

EICs or EI coins or tradeable currencies or points for learning productsmeans a point or monetary entity associated with learning products.

In an example, the present invention provides a trustworthyauthentication technique. In an example, the technique is foruniversities and colleges (that contain the key expertise andscholarship) to qualify, codify and ratify information that is“canonical” and therefore meritorious of inclusion in higher education.In an example, all institutions, courses, or instructors will go throughaccreditation, which of course is run by the members of the system, notan outside entity.

In an example, the technique provides for creating a block chain ofuniversities or colleges or entities that have been authenticated andaccredited. In an example, other aspects that can be configured into ablock chain include, but are not limited to, course materials,transcripts, matriculation data, and other information. Rather thanbeing in a central repository, any and all such information will bedistributed on a public ledger across a world wide network of computersin an encrypted manner. A key will allow an authorized entity to accesssuch information using conditions if needed, such as time, place, andduration. Of course, there can be other variations, modifications, andalternatives.

FIG. 1A is a simplified diagram of a meta processing system for learningaccording to an example of the present invention. As shown, the systemhas a course module, which includes templates, video, and otherinformation. The course can be directed to a variety of subjectsincluding but not limited to science, math, English, history,psychology, engineering, business, finance, accounting, or any othercollege course subject.

As shown, the course module is configured with a plurality of sensordevices, an image capturing device, data input device, virtual reality(VR) (including augmented reality, mixed reality), or the like. In anexample, the sensor devices or plurality of external data capturingdevices comprises a camera, a keyboard, an accelerometer sensor, an rfsensor, a gyroscope, a chemical sensor, a temperature sensor, amicrophone, VR device, or other input device. Of course, there can beother variations, modifications, and alternatives.

In an example, the system has a meta processor. The meta processorincludes an artificial intelligence process, a natural language process,and neural net process each of which can be run configured with eachother or independently from each other.

In an example, the invention provides a method of using the meta moduleprocess of capturing data and processing the data for feedback to auser, e.g., learner, student, or other human entity. In an example, themethod includes providing information related to a course in a firstformat. In an example, the course can be sourced from an off-lineclass-room course.

In an example, the method includes transferring the information in thefirst format to a server device. The server device can ben coupled to aplurality of computers on a world wide network of computers, such as theInternet. In an example, the method includes storing the information inthe first format into a memory resource coupled to the server device.

In an example, the method includes processing the information related tothe course on the server device to convert the course into a secondformat, the second format comprising a plurality of templates and avideo. The second format is suitable for using the course in an on-linemanner.

The method configures the course in the second format with a metamodule. As noted, the meta module comprises an artificial intelligencemodule. In an example, the artificial intelligence module comprises aplurality of input interfaces each of the input interfaces coupled to anode. In an example, each of the nodes comprises a weighing function. Inan example, each of the nodes is coupled to an output interface.

In an example, the artificial intelligence module comprises a neuralnetwork process configured on a neural network process, wherein theplurality of nodes comprises at least 1 million nodes. In an example,the artificial intelligence module comprises a neural network processconfigured on a processing device.

In an example, the method includes configuring the course coupled to theartificial intelligence module to a plurality of external data capturingdevices. Each of the plurality of external data captures devices beingspatially disposed on a mobile computing device. In an example, themobile computing device is coupled to the world wide network ofcomputers.

In an example, the method includes initiating use of the course in thesecond format coupled to the artificial intelligence module from themobile computing device and capturing data from a user of the mobilecomputing device from each of the plurality of external data capturingdevices, while the user is actively interacting with the course in thesecond format from the mobile computing device.

In an example, the method includes transferring data from each of theplurality of external data capturing devices from the mobile computingdevice to the artificial intelligence module and, thereafter, outputtinga feedback from the artificial intelligence module to the user of thecourse.

In an example, the method also includes finalizing use of the course inthe second format; and initiating a test associated with the course.Optionally, the method includes finalizing use of the course in thesecond format; initiating a test associated with the course; passing thetest; and transferring a credit for the course to the user of the mobiledevice and the course. Of course, there can be other variations,modifications, and alternatives.

Optionally, the method can also includes transferring spatial movementinformation from a wearable device to the mobile computing device. Thewearable device can be a watch, a suit, a vest, a headset, a pair ofglasses, a pair of pants, shoes, or other wearable device. The wearabledevice can include a plurality of sensing devices spatially disposed onthe device. A wireless or wired transceiver or transmitter can transmitinformation from each of the sensors to the meta processor.

In an example, the method includes finalizing use of the course in thesecond format. The method includes initiating a test associated with thecourse and passing the test (or taking it over if the user does not passthe course). The method includes transferring a credit for the course tothe user of the mobile device and the course, configuring the creditwith a time and date stamp and other information into a block ofinformation, and adding the block of information into a chain of otherblocks of information to form a block chain associated with the user inan encrypted format distributed on a public ledger configurationprovided on a world wide network of computers.

In an example, the course module and other elements can be implementedusing a mobile device. In an example, the mobile device is a lap topcomputer, a tablet, an iPad, a Smart phone, or other mobile device. Ofcourse, there can be other variations, modifications, and alternatives.

In an alternative example, the present invention provides a meta dataprocessing apparatus for processing sensor inputs and providing feedbackto a user for an on-line course. The apparatus has a housing configuredwith a display device. In an example, the display device is coupled toan input device for communicating text information from a user. Thedevice has a processing device, such as a central processing unit,graphics processing unit, digital signal processing unit, microcontroller or others.

In an example, the apparatus has a network interface coupled to theprocessing device. In an example, the network interface is configured tocouple to a world wide network of computers or a local network ofcomputers. The apparatus has a memory resource coupled to the processingdevice and an application comprising a course module. In an example, thecourse module comprises a plurality of templates and at least one videofile, and processes, each of which may be desirably tailored to a userbased upon feedback from various processing modules.

In an example, the apparatus has an image capturing device coupled tothe housing and configured to the processing device. In an example, theimage capturing device is configured to capture an image of at least afacial expression in a first format of the user while interacting withthe course module. The image capturing device can be a high-resolutioncamera that is suitable for capturing the image and has sufficientpixels to be processed.

In an example, the apparatus has a plurality of sensors for identifyinga spatial orientation of the user while interacting with the coursemodule. In an example, the sensor devices or plurality of external datacapturing devices comprises a camera, a keyboard, an accelerometersensor, an rf sensor, a gyroscope, a chemical sensor, a temperaturesensor, a microphone, or other input device. Of course, there can beother variations, modifications, and alternatives.

In an example, the apparatus has a natural language processor configuredfor processing information from the text information while the user isinteracting with the course module. In an example, the natural languageprocessor is configured to process the text information to identify acharacteristic of the user in association with the course. Additionally,the apparatus has an artificial intelligence module coupled to theprocessing device. In an example, the artificial intelligence modulecomprises a neural network module comprising a plurality of nodes. In anexample, the plurality of nodes can be numbered from 1-N, where N is aninteger greater than 10 and less than 10,000,000, and possibly greater,depending upon the example. The plurality of nodes are coupled torespective sensors, image capturing device, natural language processor,or other information receiving devices, and an output. Of course, therecan be other variations, modifications, and alternatives.

In an example, the apparatus has an output handler coupled to the outputof the neural network module, the output handler configured to providefeedback to the user. The feedback comprises a plurality ofcharacteristics to allow the user to achieve a predetermined scorewithin a range for the course.

In an example, the course is related to science, math, English, history,psychology, engineering, business, finance, accounting, or any othercollege course subject.

In an example, the apparatus includes a wearable device comprising a setof sensors to characterize movement, orientation, temperature, heartrate, breathing rate, oxygen, and other parameters of the user whileinteracting with the course, the wearable device being coupled to aninput of the artificial intelligence module.

In an example, the housing is shock proof.

In an example, the neural network module is configured to receiveinformation from the image capturing device and output a learningcharacteristic of the user.

In an example, the neural network module is configured to receiveinformation associated with a facial expression and an eye response fromthe image capturing device and output a learning characteristic of theuser.

In an example, the method includes transferring a spatial locationinformation and a time information to the artificial intelligencemodule.

In a preferred example, an output handler coupled to the output of theneural network module, the output handler configured to provide feedbackto the user and configure the Myamesite™ course. The myamesite coursehas been configured with feedback to create a specialized orpersonalized course for the user or student. Further details of thepresent method, apparatus, and system can be found throughout thepresent specification and more particularly below.

FIG. 1 is a simplified diagram with a network system according to anexample of the present invention. As shown, the network system has acourse module, which is coupled to a client device 109, which is coupledto a world wide network of computers, such as the Internet 111. In anexample, the Internet comprises a plurality of server devices 113coupled to memory resource 115 or database. The system also includes aplurality of servers configured with a plurality of block chaininformation, as shown.

In an example, the block chain information can be provided by ablockchain formation, which can be described in Wikipedia.com. In anexample, a main chain consists of the longest series of blocks from thegenesis block to the current block. Orphan blocks exist outside of themain chain. In an example, a blockchain is a growing list of records,called blocks, which are linked using cryptography. Each block containsa cryptographic hash of the previous block, a timestamp, and transactiondata (generally represented as a merkle tree root hash or other type ofhash or configuration). By design, a blockchain is resistant tomodification of the data. The blockchain is an open, distributed ledgerthat can record transactions between two parties efficiently and in averifiable and permanent way. For use as a distributed ledger, ablockchain is typically managed by a peer-to-peer network collectivelyadhering to a protocol for inter-node communication and validating newblocks. Once recorded, the data in any given block cannot be alteredretroactively without alteration of all subsequent blocks, whichrequires consensus of the network majority. Although blockchain recordsare not unalterable, blockchains may be considered secure by design andexemplify a distributed computing system with high Byzantine faulttolerance. Decentralized consensus has therefore been claimed with ablockchain. Of course, there can be other variations, modifications, andalternatives.

FIG. 2 is a more detailed diagram of a processing engine with inputdevices according to an example of the present invention. In an example,the processing engine 201 is coupled to input devices 203, 205, 207,209, 211, 214, among others. The processing engine interfaces with amemory resource, such as storage 215.

In an example, the processing engine is configured with a meta dataprocessing apparatus for processing sensor inputs and providing feedbackto a user for an on-line course. The apparatus has a housing configuredwith a display device. In an example, the display device is coupled toan input device for communicating text information from a user. Thedevice has a processing device, such as a central processing unit,graphics processing unit, digital signal processing unit, microcontroller or others.

In an example, the apparatus has a network interface 207 coupled to theprocessing device. In an example, the network interface is configured tocouple to a world wide network of computers or a local network ofcomputers. The apparatus has a memory resource 215 coupled to theprocessing device and an application comprising a course module. In anexample, the course module comprises a plurality of templates and atleast one video file, and processes, each of which may be desirablytailored to a user based upon feedback from various processing modules.

In an example, the apparatus has an image capturing device coupled tothe housing and configured to the processing device. In an example, theimage capturing device is configured to capture an image of at least afacial expression in a first format of the user while interacting withthe course module. The image capturing device can be a high resolutioncamera that is suitable for capturing the image and has sufficientpixels to be processed.

In an example, the apparatus has a plurality of sensors for identifyinga spatial orientation of the user while interacting with the coursemodule. In an example, the sensor devices or plurality of external datacapturing devices comprises a camera, a keyboard, an accelerometersensor, an rf sensor, a gyroscope, a chemical sensor, a temperaturesensor, a microphone, or other input device. Of course, there can beother variations, modifications, and alternatives.

In an example, the apparatus has a natural language processor configuredfor processing information from the text information while the user isinteracting with the course module. In an example, the natural languageprocessor is configured to process the text information to identify acharacteristic of the user in association with the course. Additionally,the apparatus has an artificial intelligence module coupled to theprocessing device. In an example, the artificial intelligence modulecomprises a neural network module comprising a plurality of nodes. In anexample, the plurality of nodes can be numbered from 1-N, where N is aninteger greater than 10 and less than 10,000,000, and possibly greater,depending upon the example. The plurality of nodes are coupled torespective sensors, image capturing device, natural language processor,or other information receiving devices, and an output. Of course, therecan be other variations, modifications, and alternatives.

In an example, the apparatus has an output handler coupled to the outputof the neural network module, the output handler configured to providefeedback to the user. The feedback comprises a plurality ofcharacteristics to allow the user to achieve a predetermined scorewithin a range for the course.

In an example, the course is related to science, math, English, history,psychology, engineering, business, finance, accounting, or any othercollege course subject.

In an example, the apparatus includes a wearable device comprising a setof sensors to characterize movement, orientation, temperature, heartrate, breathing rate, oxygen, and other parameters of the user whileinteracting with the course, the wearable device being coupled to aninput of the artificial intelligence module.

In an example, the housing is shock proof.

In an example, the neural network module is configured to receiveinformation from the image capturing device and output a learningcharacteristic of the user.

In an example, the neural network module is configured to receiveinformation associated with a facial expression and an eye response fromthe image capturing device and output a learning characteristic of theuser.

In an example, the method includes transferring a spatial locationinformation and a time information to the artificial intelligencemodule.

In a preferred example, the an output handler coupled to the output ofthe neural network module, the output handler configured to providefeedback to the user and configure the Myamesite™ course. The myamesitecourse has been configured with feedback to create a specialized orpersonalized course for the user or student.

FIG. 3 is a more detailed diagram of a processing system 300 accordingto an example of the present invention. As shown, the system has a bus301 that communicates with input output devices 307, 309, 313. The inputoutput devices is coupled to camera 303, sensors 311, and internalsensors 305. The bus also has communication module 315, a digital signalprocessor 317, other input output devices 323, memory resource 319, andmicroprocessor 321. The bus also communications with course module 350,which has been previously explained throughout this specification.

In an example, the system also has a block chain process and relatedblock chain information 355 that is distributed through a network. In anexample, the system can take learning data, and perform a block chainprocess, including encryption and distribution for public or selectiveviewing.

In an example, the system can be configured using a secure learningexperience using an encrypted encoded network. In an example, the methodincludes configuring information using a course module derived from aninteractive course platform coupled to a server and a network. In anexample, the course module comprises information provided from a humanuser coupled to a plurality of sensing devices, including at least animage capturing device, a motion sensor, and an ambient sensor. Forsecurity, the method assigns a time and date stamp on the course module,and then processes information using the course module to validate itagainst a predetermined quality metric, coding format, and ratificationinformation to configure a second course module in a canonical format.In an example, the method processes information using the course modulein the second format using an encryption process. The method thenconfigures information using the course module on a public ledge in ablock chain configuration.

FIG. 4 is a more detailed diagram of an alternative processing system400 according to an example of the present invention. As shown, thesystem has a bus that communicates to a sensor array 403, which includesboth passive sensors 407 and active sensors 409. The bus also has inputoutput device 405, processor 411, memory resource 413, which is coupledto mass storage 415 including documents, templates, and otherconfigurations. A course module 350 is coupled to the bus. In anexample, the system also has a block chain process and related blockchain information 355 that is distributed through a network. In anexample, the system can take learning data, and perform a block chainprocess, including encryption and distribution for public or selectiveviewing.

FIG. 5 is a more detailed diagram of an alternative processing system500 according to an example of the present invention. As shown, thesystem has a bus that communicates to a sensor array 403, which includesboth passive sensors 407 and active sensors 409. The bus also has inputoutput device 405, processor 511, which can include artificialintelligence processors, digital signal processors, and otherprocessors, memory resource 413, which is coupled to mass storage 415including documents, templates, and other configurations. An artificialintelligence module 501 is also coupled to the memory resource. Theartificial intelligence module includes configurations that are learnedand used in accordance to this example with the course module 350. Acourse module is coupled to the bus. In an example, the system also hasa block chain process and related block chain information 355 that isdistributed through a network. In an example, the system can takelearning data, and perform a block chain process, including encryptionand distribution for public or selective viewing.

FIG. 6 is a simplified flow diagram 600 of an integrated data processingprocess according to an example of the present invention. In an example,the method begins with start, step 601. In an example, the inventionprovides a method of using the meta module process of capturing data andprocessing the data for feedback to a user, e.g., learner, student, orother human entity. In an example, the present process provides for asingle integrated application to perform various processes that can beimplemented using a combination of hardware and software. In an example,the method includes providing information related to a course in a firstformat, such as a video, a text book, or any combination thereof. In anexample, the course can be sourced from an off-line class-room course.

In an example, the method includes transferring the information in thefirst format to a server device. The server device can be coupled to aplurality of computers on a world wide network of computers, such as theInternet. In an example, the method includes storing the information inthe first format into a memory resource coupled to the server device.

In an example, the method includes processing the information related tothe course on the server device to convert the course into a secondformat, the second format comprising a plurality of templates and avideo. The second format is suitable for using the course in an on-linemanner through the Internet and client devices.

The method configures the course in the second format with a metamodule. As noted, the meta module comprises an artificial intelligencemodule. In an example, the artificial intelligence module comprises aplurality of input interfaces each of the input interfaces coupled to anode. In an example, each of the nodes comprises a weighing function. Inan example, each of the nodes is coupled to an output interface.

In an example, the artificial intelligence module comprises a neuralnetwork process configured on a neural network process, wherein theplurality of nodes comprises at least 1 million nodes. In an example,the artificial intelligence module comprises a neural network processconfigured on a processing device.

In an example, the method initiates 603 capturing data from a pluralityof sensing devices, which can be internal or external, passive, oractive in an example, to teach the neural network process including theplurality of nodes with selected weighing functions.

In an example, the method includes configuring 605 the course coupled tothe artificial intelligence module to a plurality of external datacapturing devices, each of the devices being associated with a weighingfunction for the neural network process. Each of the plurality ofexternal data captures devices being spatially disposed on a mobilecomputing device or other device. In an example, the mobile computingdevice is coupled to the world wide network of computers.

In an example, the method includes initiating 607 use of the course inthe second format coupled to the artificial intelligence module from themobile computing device, among other client devices, and capturing datafrom a user of the mobile computing device from each of the plurality ofexternal data capturing devices, while the user is actively interactingwith the course in the second format from the mobile computing device.

In an example, while using the module associated with the course, if anyrules and/or decisions related to neural network process is triggered,step 609, the method processes information 613 associated with suchrules and/or decisions, and provides feedback 615 to the user in anexample. As further shown, n an example, the method includestransferring data from each of the plurality of external data capturingdevices from the mobile computing device to the artificial intelligencemodule and, thereafter, outputting a feedback 615 from the artificialintelligence module to the user of the course.

In an example, the method also includes finalizing use of the course inthe second format; and initiating a test associated with the course.Optionally, the method includes finalizing use of the course in thesecond format; initiating a test associated with the course; passing thetest; and transferring a credit for the course to the user of the mobiledevice and the course. The method ends at stop, step 621. Of course,there can be other variations, modifications, and alternatives.

Optionally, the method can also includes transferring spatial movementinformation from a wearable device to the mobile computing device. Thewearable device can be a watch, a suit, a vest, a headset, a pair ofglasses, a pair of pants, shoes, or other wearable device. The wearabledevice can include a plurality of sensing devices spatially disposed onthe device. A wireless or wired transceiver or transmitter can transmitinformation from each of the sensors to the meta processor.

In an example, the course module and other elements can be implementedusing a mobile device. In an example, the mobile device is a lap topcomputer, a tablet, an iPad, a Smart phone, or other mobile device. Ofcourse, there can be other variations, modifications, and alternatives.

In an example, various hardware elements of the invention can beimplemented using a smart phone with a capture image of a user accordingto an embodiment of the present invention. As shown, the smart phoneincludes a housing, display, and interface device, which may include abutton, microphone, or touch screen. Preferably, the phone has ahigh-resolution camera device, which can be used in various modes. Anexample of a smart phone can be an iPhone from Apple Computer ofCupertino Calif. Alternatively, the smart phone can be a Galaxy fromSamsung or others.

In an example, the smart phone includes the following features (whichare found in an iPhone from Apple Computer, although there can bevariations), see www.apple.com, which is incorporated by reference. Inan example, the phone can include 802.11b/g/n Wi-Fi (802.11n 2.4 GHzonly), Bluetooth 2.1+EDR wireless technology, Assisted GPS, Digitalcompass, Wi-Fi, Cellular, Retina display, 5-megapixel iSight camera,Video recording, HD (720p) up to 30 frames per second with audio, Photoand video geotagging, Three-axis gyro, Accelerometer, Proximity sensor,and Ambient light sensor. Of course, there can be other variations,modifications, and alternatives.

An exemplary electronic device may be a portable electronic device, suchas a media player, a cellular phone, a personal data organizer, or thelike. Indeed, in such embodiments, a portable electronic device mayinclude a combination of the functionalities of such devices. Inaddition, the electronic device may allow a user to connect to andcommunicate through the Internet or through other networks, such aslocal or wide area networks. For example, the portable electronic devicemay allow a user to access the internet and to communicate using e-mail,text messaging, instant messaging, or using other forms of electroniccommunication. By way of example, the electronic device may be a modelof an iPod having a display screen or an iPhone available from AppleInc.

In certain embodiments, the device may be powered by one or morerechargeable and/or replaceable batteries. Such embodiments may behighly portable, allowing a user to carry the electronic device whiletraveling, working, exercising, and so forth. In this manner, anddepending on the functionalities provided by the electronic device, auser may listen to music, play games or video, record video or takepictures, place and receive telephone calls, communicate with others,control other devices (e.g., via remote control and/or Bluetoothfunctionality), and so forth while moving freely with the device. Inaddition, device may be sized such that it fits relatively easily into apocket or a hand of the user. While certain embodiments of the presentinvention are described with respect to a portable electronic device, itshould be noted that the presently disclosed techniques may beapplicable to a wide array of other, less portable, electronic devicesand systems that are configured to render graphical data, such as adesktop computer.

In the presently illustrated embodiment, the exemplary device includesan enclosure or housing, a display, user input structures, andinput/output connectors. The enclosure may be formed from plastic,metal, composite materials, or other suitable materials, or anycombination thereof. The enclosure may protect the interior componentsof the electronic device from physical damage, and may also shield theinterior components from electromagnetic interference (EMI).

The display may be a liquid crystal display (LCD), a light emittingdiode (LED) based display, an organic light emitting diode (OLED) baseddisplay, or some other suitable display. In accordance with certainembodiments of the present invention, the display may display a userinterface and various other images, such as logos, avatars, photos,album art, and the like. Additionally, in one embodiment, the displaymay include a touch screen through which a user may interact with theuser interface. The display may also include various function and/orsystem indicators to provide feedback to a user, such as power status,call status, memory status, or the like. These indicators may beincorporated into the user interface displayed on the display.

In an embodiment, one or more of the user input structures areconfigured to control the device, such as by controlling a mode ofoperation, an output level, an output type, etc. For instance, the userinput structures may include a button to turn the device on or off.Further the user input structures may allow a user to interact with theuser interface on the display. Embodiments of the portable electronicdevice may include any number of user input structures, includingbuttons, switches, a control pad, a scroll wheel, or any other suitableinput structures. The user input structures may work with the userinterface displayed on the device to control functions of the deviceand/or any interfaces or devices connected to or used by the device. Forexample, the user input structures may allow a user to navigate adisplayed user interface or to return such a displayed user interface toa default or home screen.

The exemplary device may also include various input and output ports toallow connection of additional devices. For example, a port may be aheadphone jack that provides for the connection of headphones.Additionally, a port may have both input/output capabilities to providefor connection of a headset (e.g., a headphone and microphonecombination). Embodiments of the present invention may include anynumber of input and/or output ports, such as headphone and headsetjacks, universal serial bus (USB) ports, IEEE-1394 ports, and AC and/orDC power connectors. Further, the device may use the input and outputports to connect to and send or receive data with any other device, suchas other portable electronic devices, personal computers, printers, orthe like. For example, in one embodiment, the device may connect to apersonal computer via an IEEE-1394 connection to send and receive datafiles, such as media files. Further details of the device can be foundin U.S. Pat. No. 8,294,730, assigned to Apple, Inc.

In embodiments of the present invention, various uses of blockchaincoding may provide authentication and verification of the educationprocess. For example, course materials provided directly from aninstitution (e.g. lecturer, professor) or the modified course materialsprovided to the user using embodiments of the present invention may beencoded into a first block (not necessarily the ordinal first block) ina block chain. In various embodiments, the authentication may alsoinclude proof of accreditation of the course and/or the institutionitself. In some embodiments, prior to hashing, the materials may beencoded with a provider private key. It is contemplated that the firstblock can help verify the materials provide to the user are genuine andauthorized.

In some embodiments, education materials provided to the user arecustomized for each user, for example, by adding the user's name,address, student identifier, or the like to the documents, videos, etc.Accordingly, the blockchain hash of educational materials for differentusers should also be different. Such techniques are usable inembodiments where course materials are highly valuable, and onlystudents who enroll in the course should be able to receive credit orcertification for the course. In such cases, if a third-party attemptsuse the course materials without registering, the third party cannotreceive accreditation for the course. This is because the blockcorresponding to the course materials in the third party's blockchainwill not be authenticated with the third party's name.

Next, in various embodiments, if a user completes a course successfully,an additional block is added to the blockchain. The blockchain hash maybe performed upon the student data (e.g. name, student ID, course, time,etc.), one or more certificates of completion, course information (e.g.institution name, professor name, course name, credit hours, etc.),grade, and the like. In various embodiments, the user may beauthenticated by other means, such as social security number, privatekey, password, or the like. In various embodiments, the new blockincludes a hash of the previous block (e.g. proof that the educationmaterials used were authorized) plus the hash of the above userinformation. As a result, the blockchain can be used to prove that theauthorized user completed a specific course authorized by a specificaccredited institution.

In various embodiments of the present invention, as a user repeats theabove process for different courses, additional blocks are added to theblockchain. The blockchain thus can verify the user's credits, grades,etc.; can verify that the course was provided by an authorizedinstitution, and can verify that the user was authorized to take thecourse. In various embodiments, various educational providers,educational institutions, and other distributed stakeholders by storeblockchains geared towards educational achievements.

In some embodiments, transactions within the process described above mayalso include payment information. In various embodiments, paymentinformation may be made using available coin offerings. In otherembodiments, payment information may be made using a custom coinoffering directed to education on all different levels, education frominstitutions of higher learning, offerings in conjunction witheducational 529 plans, and the like. The inventor is not currently awareof such educationally-directed coin offerings, but believes they may beused in various embodiments of the present invention.

In an example, the invention also includes a method for a securelearning experience using a encrypted encoded network. The methodincludes configuring a course module information (e.g., useridentification, course, pass or non-pass results, and other information)derived from an interactive course platform coupled to a server and anetwork. In an example, the course module comprises information providedfrom a human user coupled to a plurality of sensing devices, includingat least an image capturing device, a motion sensor, and an ambientsensor. The method includes assigning a time and date stamp on thecourse module and processing the course module to validate it against apredetermined quality metric, coding format, and ratificationinformation to configure a second course module in a canonical format.The method includes processing the course module in the second formatusing an encryption process and configuring the course module on apublic ledge in a block chain configuration.

Having described various embodiments, examples, and implementations, itshould be apparent to those skilled in the relevant art that theforegoing is illustrative only and not limiting, having been presentedby way of example only. Many other schemes for distributing functionsamong the various functional elements of the illustrated embodiment orexample are possible. The functions of any element may be carried out invarious ways in alternative embodiments or examples.

Also, the functions of several elements may, in alternative embodimentsor examples, be carried out by fewer, or a single, element. Similarly,in some embodiments, any functional element may perform fewer, ordifferent, operations than those described with respect to theillustrated embodiment or example. Also, functional elements shown asdistinct for purposes of illustration may be incorporated within otherfunctional elements in a particular implementation. Also, the sequencingof functions or portions of functions generally may be altered. Certainfunctional elements, files, data structures, and so one may be describedin the illustrated embodiments as located in system memory of aparticular or hub. In other embodiments, however, they may be locatedon, or distributed across, systems or other platforms that areco-located and/or remote from each other. For example, any one or moreof data files or data structures described as co-located on and “local”to a server or other computer may be located in a computer system orsystems remote from the server. In addition, it will be understood bythose skilled in the relevant art that control and data flows betweenand among functional elements and various data structures may vary inmany ways from the control and data flows described above or indocuments incorporated by reference herein. More particularly,intermediary functional elements may direct control or data flows, andthe functions of various elements may be combined, divided, or otherwiserearranged to allow parallel processing or for other reasons. Also,intermediate data structures of files may be used and various describeddata structures of files may be combined or otherwise arranged.

In other examples, combinations or sub-combinations of the abovedisclosed invention can be advantageously made. The block diagrams ofthe architecture and flow charts are grouped for ease of understanding.However it should be understood that combinations of blocks, additionsof new blocks, re-arrangement of blocks, and the like are contemplatedin alternative embodiments of the present invention.

The specification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that various modifications and changes may be made thereuntowithout departing from the broader spirit and scope of the invention asset forth in the claims.

The invention claimed is:
 1. A method for operating a meta system forprocessing sensor inputs and providing feedback to a user for an on-linecourse, to configure the online course, and to distribute the on linecourse on a block chain, the method comprising: in the meta systemcomprising: an apparatus comprising: a housing configured with a displaydevice, the display device coupled to an input device for communicatingtext information from the user; a processing device; a network interfacecoupled to the processing device, the network interface being configuredto couple to a world wide network of computers or a local network ofcomputers; a memory resource coupled to the processing device; anapplication comprising a course module, the course module comprising aplurality of templates and at least one video file; an image capturingdevice coupled to the housing and configured to the processing device,the image capturing device being configured to capture an image of atleast a facial expression in a first format of the user whileinteracting with the course module; a plurality of sensors foridentifying a spatial orientation of the user while interacting with thecourse module; a natural language processor configured for processinginformation from the text information while the user is interacting withthe course module; an artificial intelligence module coupled to theprocessing device, the artificial intelligence module comprising aneural network module comprising a plurality of nodes, the plurality ofnodes being numbered from 1-N, where N is an integer greater than 10 andless than 10,000,000, the plurality of nodes being coupled to respectivesensors, image capturing device, natural language processor, or otherinformation receiving devices, and an output; an output handler coupledto the output of the neural network module, the output handlerconfigured to provide the feedback to the user and configure the on linecourse; and a block chain provided on a public ledger, the block chaininclude information associated with the user and the on line course;using the meta system to process information associated with the userand the on line course on the block chain.
 2. The method of claim 1wherein the feedback comprises a plurality of characteristics to allowthe user to achieve a predetermined score within a range for the course;wherein the on line course comprises a personally designed course basedupon the feedback to the user.
 3. The method of claim 1 wherein thenatural language processor is configured to process the text informationto identify a characteristic of the user in association with the course.4. The method of claim 1 wherein the plurality of nodes comprises atleast 1 million nodes; and wherein the plurality of sensors comprises acamera, a keyboard, an accelerometer sensor, an rf sensor, a gyroscope,a chemical sensor, a temperature sensor, a microphone, or other inputdevice.
 5. The method of claim 1 wherein the course is related toscience, math, English, history, psychology, engineering, business,finance, accounting, or any other college course subject.
 6. The methodof claim 1 further comprising a wearable device comprising a set ofsensors to characterize movement, orientation, temperature, heart rate,breathing rate, oxygen, and other parameters of the user whileinteracting with the course, the wearable device being coupled to aninput of the artificial intelligence module.
 7. The method of claim 1wherein the housing is shock proof.
 8. The method of claim 1 wherein theneural network module is configured to receive information from theimage capturing device and output a learning characteristic of the user.9. The method of claim 1 wherein the neural network module is configuredto receive information associated with a facial expression and an eyeresponse from the image capturing device and output a learningcharacteristic of the user.
 10. The method of claim 1 further comprisinga location sensor configured to transferring a spatial locationinformation and a time information to the artificial intelligencemodule.